Intelligence Operating System
§ MULTI-UNIT
One Ontology. One Truth.
LAB Platform unifies POS, accounting, labor, inventory, and reservations into a single governed model — so your AI and your dashboards never disagree, and your GMs get the next move before the shift starts, not a report after the quarter ends.
ONTOLOGY // one shared definition of every menu item, labor hour, and location — the same facts everywhere your data lives.
05 UNIFIED
PRE-SHIFT
3 → 15 LOC
LOI SIGNED
§01 Operational Outcomes
What the system is for.
Protect MarginProtect Margin
Catch food, beverage, and labor cost drift before it erodes the P&L — not after the month closes.
Grow Topline
Turn reservation and demand signals into staffing and menu moves your GMs can act on same-shift.
Compounding IP
Every location that comes online makes the model sharper — a moat that grows with your footprint.
§02 System Architecture
Data in. Decisions out.
One integrated system, three layers — each built on the one beneath it. Raw operational data enters the foundation and leaves the top as the next move.
LAYER 01 Data Foundation
LAB Convergence™
One truth, many systems — the governed data spine everything above runs on.
Input
POS, accounting, labor, inventory, and reservations — across every location.
Function
Reconciles fragmented systems into one normalized, governed model.
Output
A single source of truth — one ontology the whole platform shares.
Normalized ▼
LAYER 02 Applied AI
LAB Intelligence™
Your IP, your intelligence, inside your operation — a company-specific model trained on your proprietary data.
Input
The unified data spine, plus your operating context and history.
Function
Reasons over your data in your own operational language.
Output
Forecasts, anomaly flags, and answers — not generic model guesses.
Reasoned ▼
LAYER 03 Decision Layer
LAB Visualize™
Input
The intelligence layer’s forecasts, flags, and answers.
Function
Turns them into live operational views built to drive action.
Output
The next move — before the shift starts, in the GM’s hands.
Closing the Loop — Next
Visualize is built to extend from views into action: approvable, auditable write-backs to scheduling, ordering, and pricing systems — so the next move doesn’t just get surfaced, it gets executed under GM sign-off.
§03 Access & Governance
Governed by design.
◆ SECURITY MODEL
ENFORCED ACROSS · CONVERGENCE / INTELLIGENCE / VISUALIZE
Security isn’t a fourth layer bolted on top — it’s woven through Convergence, Intelligence, and Visualize alike, for every human and every AI agent that touches your data.
Role-Based Access
Every user — human or AI — is scoped to exactly the locations and data they’re cleared to see.
SCOPE: LOCATION[*]
ROLE → GRANT ✓
DENY-BY-DEFAULT ✓
Full Audit Trail
Every forecast, view, and write-back is logged and traceable — by user, by system, by moment.
LINEAGE: SOURCE→OUTPUT
LOG: IMMUTABLE ✓
TRACE: WHO/WHAT/WHEN ✓
Your Data, Your Control
Financials and labor data live in a governed environment you control — not a shared black box.
TENANCY: ISOLATED ✓
OWNERSHIP: CLIENT
EXPORT: ON-DEMAND ✓
§04 Request a Demo
See the platform run on your own data.
We’ll stand up LAB Platform against a sample of your operation and show you the difference between a report after the quarter and the next move before the shift — and what that head start is worth to your margin.